---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: BertALL
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# BertALL

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4052
- Accuracy: 0.8834
- Precision: 0.8107
- Recall: 0.8046
- F1: 0.8040
- Top3: 0.9820
- Top3macro: 0.9594

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     | Top3   | Top3macro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|:---------:|
| 0.5593        | 1.0   | 7566  | 0.5067          | 0.8363   | 0.7252    | 0.6802 | 0.6880 | 0.9642 | 0.9173    |
| 0.3827        | 2.0   | 15132 | 0.4301          | 0.8662   | 0.7785    | 0.7760 | 0.7727 | 0.9766 | 0.9457    |
| 0.2735        | 3.0   | 22698 | 0.4170          | 0.8760   | 0.7973    | 0.7949 | 0.7920 | 0.9816 | 0.9577    |
| 0.2132        | 4.0   | 30264 | 0.4437          | 0.8846   | 0.8048    | 0.8186 | 0.8105 | 0.9828 | 0.9607    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1